This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
This paper compares the performance and efficiency of different function range interval methods for plotting f(x, y) = 0 on a rectangular region based on a subdivision scheme, whe...
Ralph R. Martin, Huahao Shou, Irina Voiculescu, Ad...
Abstract. This paper proposes an entropy based Markov chain (EMC) fusion technique and demonstrates its applications in multisensor fusion. Self-entropy and conditional entropy, wh...
This paper presents a class of neural networks suitable for the application of decoding error-correcting codes.The neural model is basically a perceptron with a high-order polynom...
: Generalized finite automata with weights for states and transitions have been successfully applied to image generation for more than a decade now. Bilevel images (black and whit...